GPU acceleration of the Seven-League Scheme for large time step simulations of stochastic differential equations
Publication date
2023-02-10
Authors
Liu, Shuaiqiang
Colonna, Graziana
Grzelak, L.A.
Oosterlee, Cornelis W.
Editors
Advisors
Supervisors
Document Type
/dk/atira/pure/researchoutput/researchoutputtypes/workingpaper/preprint
Metadata
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License
cc_by
Abstract
Monte Carlo simulation is widely used to numerically solve stochastic differential equations. Although the method is flexible and easy to implement, it may be slow to converge. Moreover, an inaccurate solution will result when using large time steps. The Seven League scheme, a deep learning-based numerical method, has been proposed to address these issues. This paper generalizes the scheme regarding parallel computing, particularly on Graphics Processing Units (GPUs), improving the computational speed.
Keywords
math.NA, cs.NA, q-fin.CP
Citation
Liu, S, Colonna, G, Grzelak, L A & Oosterlee, C W 2023 'GPU acceleration of the Seven-League Scheme for large time step simulations of stochastic differential equations' arXiv, pp. 1-5. https://doi.org/10.48550/arXiv.2302.05170